Report on Correcting Tropical Biases
Meeting
Prepared by Edwin K. Schneider
Summary
The Correcting Tropical Biases Meeting was held at the
College Park Sheraton (adjacent to COLA) in
Logistics
Venue:
Web page: www.iges.org/ctbm05
Organizing committee:
Ed Schneider (George Mason University/COLA) chair; Ed Sarachik
(
Funding: NSF, NOAA, NASA, DOE
Attendees: see Appendix 1
Exchange of Information
The discussion and proposed experiments focused on the
simulation biases in the tropical
1. Annual mean SST – cold tongue extends too far west, warm pool too cold, warm bias near S. American coast, double ITCZ, heat sources too far east.
2. Annual cycle of SST – warmest too late in the year, coldest too early, near the S. American coast where the amplitude is the largest. Indicative of too strong a semi-annual cycle.
3. ENSO – generally not well done. Amplitude biased towards western Pacific, wind stress anomalies too narrow and too far west. ENSO period short.
The experiences of several modeling groups in attempting to correct the biases were described and discussed. These are categorized and summarized below.
1. GFDL - FV gives doubled ENSO amplitude (too large), eliminates equatorward shift in subtropical jets, worse tropical simulation.
2. CCSM – FV reduces trades, heat flux.
1. GFDL – lengthens ENSO period, improves (broadens) structure, no impact on double ITCZ, reduces MJO
2.
CCSM – uncoupled simulations with
1. COLA – lowering/raising cloud base reduces/increases equatorial easterly wind stress.
2. Modifying vertical profile of convective heating impacts surface winds.
3. Eliminating convective heating parameterization (deep and shallow) in three T31L18 AGCMs (COLA, CCM3, ECHAM4), with all condensation processes handled by large scale parameterization reduces double ITCZ bias, model differences, improves MJO at the expense of other problems (7°C colder tropical troposphere, unrealistic diurnal variability).
4. GFDL - moist convective adjustment in place of RAS. Reduces double ITCZ, increases ENSO damping by heat flux, better MJO.
5. Rainfall reevaporation
1. Goddard - reevaporation of precipitation in the convective parameterization provides a convenient and useful tuning parameter for AGCM. Increasing reevaporation reduces double ITCZ bias. Strong reevaporation leads to a mid-tropospheric wet bias.
2. GFDL – no sensitivity.
1.
Viscosity - reduced horizontal viscosity in ocean gives
stronger tropical instability wave
2. Background diffusivity - too large gives warm S. American coast, cool equator by affecting the thermocline structure, temperature of the upwelled water, position of upwelling. As diffusivity is made larger, more of the upwelling is along equator and less along the coast. Time scale of 10s of years (IPRC).
1.
Shortwave accounts for almost half the bias off
2. Cloud substitution gives correct annual cycle (GFDL).
1. Restoring ocean along S. American coast produces beneficial effects that spread to the central Pacific. Does not affect W. Pacific double ITCZ. Coastal biases and western extension of the cold tongue biases may be distinct problems that are due to different mechanisms (CCSM).
2. Restoring ocean structure to observed everywhere – little reduction in ENSO biases found (COLA), but gives some improvement in SI prediction (Chang).
Mechanisms
Guiding principles
Experiments
Some of the suggested experiments generated interest in several of the modeling groups. The experimental designs were left at an early stage, with details unresolved. It was decided to designate a lead for each experiment, who would attempt to perform it in a preliminary manner, and who would report within four months to the other groups on details of experimental design, feasibility, technical issues, and hopefully results. The seven ideas for experiments are described below, along with some motivation. The leads and those expressing interest in pursuing the experiments are listed in Appendix II.
1. Add estimated fluxes due to westerly wind bursts to fluxes provided to the ocean in the Western Pacific in CGCMs. The westerly wind burst parameterization should be a function of the SST, and hence the annual cycle of SST. Both mean effects (due to “westerly” wind bursts) and annual cycle of occurrence may be important. The mean westerlies could alleviate the easterly bias in the western Pacific zonal wind stress and the SST cold bias in that region. The dependence on SST could lead to changes in the ENSO properties, e.g. amplitude.
2. Explore sensitivity of AGCM and coupled simulations of the ITCZ/SPCZ to rainfall re-evaporation. Since the double ITCZ is sensitive to rainfall reevaporation (GMAO), it may be possible to reduce the double ITCZ bias in other AGCMs, and possibly to reduce the equatorial cold bias as well.
3. “Correct” the temperature of upwelling waters in the ocean in coupled simulations.
3a) Equatorial Pacific (away from coasts)
3b) Tropical Pacific near S. American coast
If the warm bias in the E Pacific and equatorial cold bias in the E/W Pacific are caused by biases in the structure of the thermocline (e.g. too diffuse) and/or problems in the diffusive heating parameterization (e.g. too strong), then the outcome of correcting these problems in the context of the CGCM can be examined by correcting the temperature of the upwelling waters. One way to do this is to modify the vertical advection operator, so that, for example, the temperatures used in this operator are displaced vertically from the vertical velocity. That is, a parcel could advect temperatures displaced, for example, 10m above the velocity level. A more consistent alternative approach is to reduce the background diffusivity in the OGCM, which can also be expected to modify the current distribution.
4. Suppress deep convection in regions of incorrect double ITCZ (SE Pacific). A number of methods were discussed to artificially suppress moist convection. Even in the most extreme case, with convection not parameterized, the AGCM produces stable results that are physically consistent in terms of the large scale budgets. In this experiment, deep moist convection will be suppressed in the E. Pacific south of the equator in the CGCM, eliminating the double ITCZ. The hypothesis is that this may reduce the equatorial easterly bias, thereby reducing the equatorial cold bias. In addition, biases in the dynamical structures associated with ENSO, such as the structures of precipitation and wind stress anomalies, could be reduced, leading to improved ENSO simulations.
5. Increase low level (below 500m) vertical resolution in AGCM. Increased vertical resolution in the boundary layer has been found to improve the double ITCZ bias.
6. Examine AGCM+mixed layer ocean response to warming of the tropical troposphere (without corresponding surface warming). The idea is to stabilize the atmospheric vertical temperature profile of the atmosphere as seen by the deep convection parameterizations, with values similar to those that occur in simulations with increasing CO2. However the warming of surface temperature will not be included. This will stabilize the atmosphere to moist convection and allow comparison of moist convective feedbacks on the moisture budget and atmospheric dynamics.
7. Relate specific initial errors in AGCM/CGCM simulations to biases. There is significant information on tropical biases in the initial tendencies of models. In the atmosphere, this information may be apparent at the first time step of a simulation, while in the CGCM the first month may be the appropriate initial period. The plan is to collect and analyze in detail the initial tendencies, especially from the heat budget, in control runs of CGCMs. The diagnostic intervals of every half hour for the 1st day and every day for the first 100 were suggested. If these can be related simply to the eventual biases, then the process of testing bias corrections can be made more efficient. Additionally, the structure of the initial tendencies in the budget equations may give clues as to how to correct the biases.
Diagnostics
i. Nino3, Nino3.4, Nino4, lat/lon SST variance
ii. Seasonal cycle of SST variance
iii. Western extent and horseshoe pattern sign reversal
iv. Extratropical response
v. SSTA (Nino3.4) vs. zonal wind stress
vi. SSTA vs. precip.
vii. SSTA vs. SLP
viii. SSTA vs. heat flux components (SW, LW, LHF)
ix. Measures of duration of events, such as global maps of one month autocorrelations of SST
x. Depth of 20°C isotherm in ocean
Actions
The lead investigators are taking responsibility for
carrying out initial versions of the experiments in a timely manner, and for
refining the experimental design. Schneider will continue to coordinate the
activities initiated at the meeting. He will solicit, collect, and disseminate
reports on progress with these experiments in February 2006. A web page will be
maintained at COLA to provide a facility for accessing and communicating
results. A follow-up meeting is anticipated in conjunction with the 2006 CCSM
Workshop for discussion of the results and for planning further activities.
Appendix 1:
An alphabetical list of attendees and affiliation follows
Krishna Achutarao PCMDI achutarao1 AT llnl . gov
Julio Bacmeister GSFC Julio . Bacmeister . 1 AT gsfc . nasa . gov
Magdelena Balmaseda ECMWF
Anjuli Bamzai DOE Anjuli . Bamzai AT science . doe . gov
Marcelo Barreiro Princeton
Michela Biasutti LDEO biasutti AT ldeo .
Chris Bretherton UWash breth AT atmos .
Jim Carton UMd carton AT atmos . umd . edu
Ping Chang Texas A&M ping AT tamu . edu
Gokhan Danabasoglu NCAR gokhan AT ucar . edu
Jay Fein NSF jfein AT nsf . gov
Ryo Furue IPRC furue
AT
Peter Gent NCAR gent AT cgd . ucar . edu
Wayne Higgins
NCEP
Bohua Huang GMU/COLA huangb AT cola . iges . org
Ming Ji NOAA ming . ji AT noaa . gov
Fei-Fei Jin FSU jff
AT met . fsu . edu
Jim Kinter COLA kinter AT cola . iges . org
Ben Kirtman GMU/COLA kirtman AT cola . iges . org
Barry Klinger GMU klinger AT cola . iges . org
Bill Large NCAR wily AT ucar . edu
David Legler CLIVAR legler AT usclivar . org
Vasu Misra COLA misra AT cola . iges . org
Raghu Murtugudde UMd ragu AT essic . umd . edu
David Neelin UCLA neelin AT atmos . ucla . edu
Sumant Nigam UMd nigam AT atmos . umd . edu
Hua-Lu Pan NCEP Hualu . Pan AT noaa . gov
Jerry Potter PCMDI potter2 AT llnl . gov
Phil Rasch NCAR pjr AT ucar . edu
Kelvin
Richards IPRC rkelvin
AT
Tony Rosati GFDL Tony . Rosati AT noaa . gov
Ed Sarachik
Paul Schopf GMU schopf AT cola . iges . org
Ed Schneider GMU/COLA schneide AT cola . iges . org
J. Shukla GMU shukla AT cola . iges . org
Max Suarez GSFC Max . J . Suarez AT gsfc . nasa . gov
Shan Sun GISS sun AT venus2 . giss . nasa . gov
Eli Tziperman Harvard eli AT eps . harvard . edu
Roxana Wajsowicz U. of Md roxana AT atmos . umd . edu
Wanqiu Wang NCEP Wanqiu . Wang AT noaa . gov
Yuqing Wang IPRC yuqing
AT
Andrew
Wittenberg GFDL Andrew .
Zhaohua Wu COLA zhwu AT cola . iges . org
Pingping Xie NCEP Pingping . Xie AT noaa . gov
Yan Xue NCEP Yan . Xue AT noaa . gov
Jin-Yi Yu UC
Appendix
II: Planned Experiments and Participants
1. Add estimated fluxes due to westerly wind bursts to fluxes provided to the ocean in the Western Pacific.
Lead: Tziperman
Participants: CCSM (Large), GFDL (Rosati), Murtugudde, ECMWF(Balmaseda)
2. Explore sensitivity of AGCM and coupled simulations of the ITCZ/SPCZ to rainfall re-evaporation.
Lead: GMAO (Bacmeister)
Participants: COLA (Kirtman), CCSM (Rasch), GFDL (Rosati), PCMDI (Potter)
3. “Correct” the temperature of upwelling waters in the ocean in coupled simulations.
3a) Equatorial Pacific (away from coasts)
Lead: Schopf/Klinger
Participants: CCSM (Danabasoglu), IPRC (Richards), GFDL (
3b) Equatorial Pacific near S. American coast
Lead: Schopf/Klinger
Participants: CCSM (Danabasoglu), GISS (Sun), IPRC (Richards)
4. Suppress deep convection in regions of incorrect double ITCZ (SE Pacific).
Lead: CCSM (Bretherton)
Participants: IPRC (Wang), COLA (Schneider), GMAO (Bacmeister)
5. Increase low level (below 500m) vertical resolution in AGCM.
Lead: GFDL/CCSM (Rosati/Rasch)
Participants: NCEP (Pan), ECMWF (Balmaseda), GMAO (Bacmeister), COLA (Misra)
6. Examine AGCM response to warming of the tropical troposphere (without corresponding surface warming).
Lead: Neelin
Participants: GMAO (Bacmeister, Suarez), CCSM (Rasch), IPRC (Richards), GFDL (?)
7. Relate specific initial errors in AGCM/CGCM simulations to biases.
Lead: GMAO (Suarez)
Participants: NCAR (?), IPRC (Potter), GFDL (Rosati), NCEP (Pan)